Wide-field telescopes are widely utilized to observe geosynchronous objects, with low cost and high performance. In geosynchronous object detection, stars produce the most false alarms. Thus, star-suppression is required to improve the accuracy of geosynchronous object detection. However, traditional methods involve false identification and missing identification due to the significant distortion of wide-field telescopes and undersampling of faint images. Distortion could lead to the observed positions of stars deviating from their theoretical positions, while faint and undersampling images could result in inaccurate centroid extraction. In this study, a method was proposed for analyzing the motion and structural characteristics of stars, space objects, and noise, focusing on maintaining a high star identification rate and low false identification rate with the mentioned errors. First, the invariance of the star structure under the influence of projection transformation and distortion was strictly derived. Second, two types of star-pair indices were suggested. Assessment of the structural stability was added to the foundation of the centroid matching. For accurate identification of stars, the influence of dynamic distortion was effectively inhibited using the established star-structure evaluation system. Our method achieves lightweight, straightforward, and rapid detection without requiring any prior star catalog or telescope distortion model. The experiment demonstrates that the performance of the proposed method is superior to that of previous methods influenced by distortion and centroid positioning error.


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    Title :

    Star Suppression Based on Structure of Star Groups for Geosynchronous Object Detection Using Wide-Field Telescopes


    Contributors:
    Wang, Xia (author) / Li, Zhi (author) / Xu, Can (author) / Huo, Yurong (author) / Feng, Fei (author) / Qiu, Song (author) / Zheng, Kaiyuan (author) / Qiu, Jiayu (author)


    Publication date :

    2024-06-01


    Size :

    7027413 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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